Replication package for "Do Multi-Dimensional Quotas Improve Social Equality? Intersectional Representation and Group Relations" by Rachel Brule and Aliz Toth

The best environment to run this replication is R/4.4.3. 

This replication package includes the following files: 

A) codebook.xlsx - provides descriptions for the key variables used for the analysis

B) Datasets: 

1) data/dn_dta.csv: respondent-level dataset including information on quotas and attitudes towards inter-caste marriage. Source: Dunning, T. and Nilekani, J., 2013. Ethnic quotas and political mobilization: caste, parties, and distribution in Indian village councils. American Political Science Review, 107(1), pp.35-56.

2) data/dn_vill_dta.csv: village-level dataset including information on quotas and census indicators. Source: Dunning and Nilekani, 2013.

3) data/dunning_nilekani_locations_geocoded.csv: latitude/longitude information for villages included in 1)-2). 

4) data/global_quotas.dta: country-level dataset on legislative quotas. Source: Clayton, A. and Zetterberg, P., 2018. Quota shocks: Electoral gender quotas and government spending priorities worldwide. The Journal of Politics, 80(3), pp.916-932.

5) data/india_states: shapefile of the Indian state

6) data/individual_level_quotas.csv: respondent-level data from World Values Survey Round 6. The data includes information on whether the respondent is an ethnic minority based on the Minority Rights Group and whether the ethnic group benefits from legislative quotas. 

7) Karnataka_GP_ReservationHistory.dta: reservation history of villages in Karnataka. Source: Dunning and Nilekani, 2013. 

8) reds_locations_geocoded.csv: latitude/longitude information for villages included in the Rural Economic and Demographic Survey. 

9) reds.csv: responses from the Rural Economic and Demographic Survey. 

10) vdeck36.dta: information on pradhans from the Rural Economic and Demographic Survey.

In addition, running the main analysis file will also produce "REDS_matched_vscstreserv.csv" and "REDS_matched_vstreserv.csv", which are observations retained after nearest neighbour matching villages with quotas to those without. 

C) code: 

1) _1_main.R : includes the installation of packages and the functions needed for constructing the analysis datasets and for running the analysis. This R code also runs all other R scripts that produce tables and figures included in the paper. Make sure to run all the analysis scripts in the order included in _1_main.R.

2) _2_matching.R: executes nearest neighbour matching to balance villages with and without quotas. This script outputs "REDS_matched_vscstreserv.csv" and "REDS_matched_vstreserv.csv". 

3) _3_descriptives.R: produces descriptive figures and tables

4) _4_inter_caste_relations.R: produces all tables with inter-caste relations as the outcome.

5) _5_marriage.R: produces all tables with inter-caste marriage as the outcome.

6) _6_conflict.R: produces Table K.23.

7) _7_net_effect.R: produces all figures representing the net effect of quotas. 

8) _8_alternative_mech.R: produces Table L.25 and Figure L.12

9) _9_redistribution.R: produces Table L.24.

10) _10_quota_illustration.R: produces Table D.4 (which is the longer version of Table 1), illustrating quota assignment. 

11) _11_global_quotas.R: produces Figure 4. 

12) _12_candidacy.R: produces Figures H.10-H.11

Please note that Table A1, Table A2, Figure D.5, and Table I.19 are not reproduced here as they are not part of our results, rather they summarize our data and illustrate our identification strategy.


D) This readme.txt file - self explanatory. 





 